Bayesian Kernel Methods
Bayesian methods allow for a simple and intuitive representation of the function spaces used by kernel methods. This chapter describes the basic principles of Gaussian Processes, their implementation and their connection to other kernel-based Bayesian estimation methods, such as the Relevance Vector Machine.
|Collections||ANU Research Publications|
|01_Smola_Bayesian_Kernel_Methods_2003.pdf||1.18 MB||Adobe PDF||Request a copy|